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Updated: May 12, 2025

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
Published on: December 9, 2016
MSI expresso: a software for determining MSI status and detecting MSI-related transcription events from RNA
Emmanuel Tubacher1, Alexandre How-Kit2, Mourad Sahbatou1
1Laboratory for bioinformatics, Fondation Jean DAUSSET Centre d'Etude du Polymorphisme Humain, Paris, France.
Abstract:
Microsatellite instability (MSI) is becoming increasingly important in oncology as it has been reported across more than two dozen of solid cancer types. The MSI-high phenotype has long been used as a predictive and prognostic marker in colorectal cancer and has been recently approved by the FDA as a marker for immune checkpoint blockade therapy for solid cancers. Several bioinformatics tools have been developed to assess MSI status of a tumor sample using Next-Generation Sequencing (NGS) data mostly from whole genome, whole exome, and targeted gene sequencing data. While most tools available only infer the MSI status, none of them use RNA-sequencing (RNA-seq) data and provide per microsatellite expression and genotype results. We present MSI Expresso, a software which assesses the MSI status by testing the instability of a panel of 3'UTR microsatellites from RNA-seq data and also provides a detailed landscape of MSI-related events such as exon skipping, unstable coding and intronic microsatellites with a graphical output of the recurrent events. MSI Expresso's ability to detect the MSI status was assessed from RNA-seq data of 228 colon, 13 prostate and two endometrial cancer samples with known MSI status and achieved almost 100% concordant results. Thus, MSI Expresso is a new tool for MSI detection from RNA-sequencing data complementary to genomic and genetic approaches allowing to explore the consequence of MSI events on transcripts/transcriptome.
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